Big data quantification for complex decision-making:
"Many professionals are facing a monumental challenge: navigating the intricate landscape of information to make impactful choices. The sheer volume and complexity of big data have ushered in a shift, demanding innovative methodologies and frameworks. Big Data Quantification for Complex Decisio...
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA)
IGI Global
c2024
|
| Schlagworte: | |
| Online-Zugang: | DE-862 DE-863 |
| Zusammenfassung: | "Many professionals are facing a monumental challenge: navigating the intricate landscape of information to make impactful choices. The sheer volume and complexity of big data have ushered in a shift, demanding innovative methodologies and frameworks. Big Data Quantification for Complex Decision-Making tackles this challenge head-on, offering a comprehensive exploration of the tools necessary to distill valuable insights from datasets. This book serves as a tool for professionals, researchers, and students, empowering them to not only comprehend the significance of big data in decision-making but also to translate this understanding into real-world decision making.The central objective of the book is to examine the relationship between big data and decision-making. It strives to address multiple objectives, including understanding the intricacies of big data in decision-making, navigating methodological nuances, managing uncertainty adeptly, and bridging theoretical foundations with real-world applications. The book's core aspiration is to provide readers with a comprehensive toolbox, seamlessly integrating theoretical frameworks, practical applications, and forward-thinking perspectives. This equips readers with the means to effectively navigate the data-rich landscape of modern decision-making, fostering a heightened comprehension of strategic big data utilization. Tailored for a diverse audience, this book caters to researchers and academics in data science, decision science, machine learning, artificial intelligence, and related domains."-- |
| Beschreibung: | 17 PDFs (xvi, 312 Seiten) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9798369315835 |
| Zugangseinschränkungen: | Restricted to subscribers or individual electronic text purchasers. |
Internformat
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| 245 | 0 | 0 | |a Big data quantification for complex decision-making |c Chao Zhang, Wentao Li, editors. |
| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) |b IGI Global |c c2024 | |
| 300 | |a 17 PDFs (xvi, 312 Seiten) | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a electronic |2 isbdmedia | ||
| 338 | |a online resource |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Preface -- Chapter 1. Group-Oriented Multi-Attribute Decision-Making Method Based on Dominance Rough Set Theory -- Chapter 2. A Multi-Granularity Triangular Fuzzy Approach for Diabetes Blood Glucometer Selection Using PROMETHEE and Three-Way Decision -- Chapter 3. Prediction of Parkinson's Disease Severity Based on Feature Optimization -- Chapter 4. Creating a Data Lakehouse for a South African Government-Sector Learning Control Enforcing Quality Control for Incremental Extract-Load-Transform Pipe -- Chapter 5. Decision-Making Based on Partition Order Product Space -- Chapter 6. Strategy Selection and Outcome Evaluation of Change-Based Three-Way Decisions Based on Reinforcement Learning -- Chapter 7. The Extension of MAIRCA Based on Fuzzy Number: Smart Supplier Selection -- Chapter 8. Review of Chinese Text Mining in Agriculture -- Chapter 9. A Snapshot Survey of Data Acquisition Forms in Multi-Attribute Decision-Making Studies -- Chapter 10. Research on Knowledge Representation and Reasoning Based on Decision Implication -- Compilation of References -- About the Contributors -- Index. | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 520 | 3 | |a "Many professionals are facing a monumental challenge: navigating the intricate landscape of information to make impactful choices. The sheer volume and complexity of big data have ushered in a shift, demanding innovative methodologies and frameworks. Big Data Quantification for Complex Decision-Making tackles this challenge head-on, offering a comprehensive exploration of the tools necessary to distill valuable insights from datasets. This book serves as a tool for professionals, researchers, and students, empowering them to not only comprehend the significance of big data in decision-making but also to translate this understanding into real-world decision making.The central objective of the book is to examine the relationship between big data and decision-making. It strives to address multiple objectives, including understanding the intricacies of big data in decision-making, navigating methodological nuances, managing uncertainty adeptly, and bridging theoretical foundations with real-world applications. The book's core aspiration is to provide readers with a comprehensive toolbox, seamlessly integrating theoretical frameworks, practical applications, and forward-thinking perspectives. This equips readers with the means to effectively navigate the data-rich landscape of modern decision-making, fostering a heightened comprehension of strategic big data utilization. Tailored for a diverse audience, this book caters to researchers and academics in data science, decision science, machine learning, artificial intelligence, and related domains."-- |c Provided by publisher. | |
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | |a Description based on title screen (IGI Global, viewed 04/27/2024). | ||
| 650 | 0 | |a Big data. | |
| 650 | 0 | |a Decision making |x Data processing. | |
| 653 | |a Big Data Analytics. | ||
| 653 | |a Decision-Making Under Uncertainty. | ||
| 653 | |a Deep Learning Models. | ||
| 653 | |a Formal Concept Analysis. | ||
| 653 | |a Fuzzy Decision-Making. | ||
| 653 | |a Game Theory. | ||
| 653 | |a Granular Computing. | ||
| 653 | |a Intelligent Control Systems. | ||
| 653 | |a Multi-Granularity Analysis. | ||
| 653 | |a Natural Language Processing. | ||
| 653 | |a Neural Network Models. | ||
| 653 | |a Rough Set Theory. | ||
| 653 | |a Uncertainty Modeling. | ||
| 655 | 4 | |a Electronic books. | |
| 700 | 1 | |a Li, Wentao |e editor. | |
| 700 | 1 | |a Zhang, Chao |e editor. | |
| 710 | 2 | |a IGI Global, |e publisher. | |
| 776 | 0 | 8 | |i Print version: |z 9798369315828 |
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| 912 | |a ZDB-98-IGB | ||
| 049 | |a DE-862 | ||
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Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-98-IGB-00328785 |
|---|---|
| _version_ | 1826942602562240513 |
| adam_text | |
| any_adam_object | |
| author2 | Li, Wentao Zhang, Chao |
| author2_role | edt edt |
| author2_variant | w l wl c z cz |
| author_facet | Li, Wentao Zhang, Chao |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | Q - Science |
| callnumber-label | QA76 |
| callnumber-raw | QA76.9.B45 B553 2024e |
| callnumber-search | QA76.9.B45 B553 2024e |
| callnumber-sort | QA 276.9 B45 B553 42024E |
| callnumber-subject | QA - Mathematics |
| collection | ZDB-98-IGB |
| contents | Preface -- Chapter 1. Group-Oriented Multi-Attribute Decision-Making Method Based on Dominance Rough Set Theory -- Chapter 2. A Multi-Granularity Triangular Fuzzy Approach for Diabetes Blood Glucometer Selection Using PROMETHEE and Three-Way Decision -- Chapter 3. Prediction of Parkinson's Disease Severity Based on Feature Optimization -- Chapter 4. Creating a Data Lakehouse for a South African Government-Sector Learning Control Enforcing Quality Control for Incremental Extract-Load-Transform Pipe -- Chapter 5. Decision-Making Based on Partition Order Product Space -- Chapter 6. Strategy Selection and Outcome Evaluation of Change-Based Three-Way Decisions Based on Reinforcement Learning -- Chapter 7. The Extension of MAIRCA Based on Fuzzy Number: Smart Supplier Selection -- Chapter 8. Review of Chinese Text Mining in Agriculture -- Chapter 9. A Snapshot Survey of Data Acquisition Forms in Multi-Attribute Decision-Making Studies -- Chapter 10. Research on Knowledge Representation and Reasoning Based on Decision Implication -- Compilation of References -- About the Contributors -- Index. |
| ctrlnum | (CaBNVSL)slc00005827 (OCoLC)1412643165 |
| dewey-full | 005.7 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security |
| dewey-raw | 005.7 |
| dewey-search | 005.7 |
| dewey-sort | 15.7 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
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| genre | Electronic books. |
| genre_facet | Electronic books. |
| id | ZDB-98-IGB-00328785 |
| illustrated | Not Illustrated |
| indexdate | 2025-03-18T14:30:37Z |
| institution | BVB |
| isbn | 9798369315835 |
| language | English |
| oclc_num | 1412643165 |
| open_access_boolean | |
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| owner_facet | DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| physical | 17 PDFs (xvi, 312 Seiten) Also available in print. |
| psigel | ZDB-98-IGB FWS_PDA_IGB ZDB-98-IGB |
| publishDate | 2024 |
| publishDateSearch | 2024 |
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| publisher | IGI Global |
| record_format | marc |
| spelling | Big data quantification for complex decision-making Chao Zhang, Wentao Li, editors. Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) IGI Global c2024 17 PDFs (xvi, 312 Seiten) text rdacontent electronic isbdmedia online resource rdacarrier Includes bibliographical references and index. Preface -- Chapter 1. Group-Oriented Multi-Attribute Decision-Making Method Based on Dominance Rough Set Theory -- Chapter 2. A Multi-Granularity Triangular Fuzzy Approach for Diabetes Blood Glucometer Selection Using PROMETHEE and Three-Way Decision -- Chapter 3. Prediction of Parkinson's Disease Severity Based on Feature Optimization -- Chapter 4. Creating a Data Lakehouse for a South African Government-Sector Learning Control Enforcing Quality Control for Incremental Extract-Load-Transform Pipe -- Chapter 5. Decision-Making Based on Partition Order Product Space -- Chapter 6. Strategy Selection and Outcome Evaluation of Change-Based Three-Way Decisions Based on Reinforcement Learning -- Chapter 7. The Extension of MAIRCA Based on Fuzzy Number: Smart Supplier Selection -- Chapter 8. Review of Chinese Text Mining in Agriculture -- Chapter 9. A Snapshot Survey of Data Acquisition Forms in Multi-Attribute Decision-Making Studies -- Chapter 10. Research on Knowledge Representation and Reasoning Based on Decision Implication -- Compilation of References -- About the Contributors -- Index. Restricted to subscribers or individual electronic text purchasers. "Many professionals are facing a monumental challenge: navigating the intricate landscape of information to make impactful choices. The sheer volume and complexity of big data have ushered in a shift, demanding innovative methodologies and frameworks. Big Data Quantification for Complex Decision-Making tackles this challenge head-on, offering a comprehensive exploration of the tools necessary to distill valuable insights from datasets. This book serves as a tool for professionals, researchers, and students, empowering them to not only comprehend the significance of big data in decision-making but also to translate this understanding into real-world decision making.The central objective of the book is to examine the relationship between big data and decision-making. It strives to address multiple objectives, including understanding the intricacies of big data in decision-making, navigating methodological nuances, managing uncertainty adeptly, and bridging theoretical foundations with real-world applications. The book's core aspiration is to provide readers with a comprehensive toolbox, seamlessly integrating theoretical frameworks, practical applications, and forward-thinking perspectives. This equips readers with the means to effectively navigate the data-rich landscape of modern decision-making, fostering a heightened comprehension of strategic big data utilization. Tailored for a diverse audience, this book caters to researchers and academics in data science, decision science, machine learning, artificial intelligence, and related domains."-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 04/27/2024). Big data. Decision making Data processing. Big Data Analytics. Decision-Making Under Uncertainty. Deep Learning Models. Formal Concept Analysis. Fuzzy Decision-Making. Game Theory. Granular Computing. Intelligent Control Systems. Multi-Granularity Analysis. Natural Language Processing. Neural Network Models. Rough Set Theory. Uncertainty Modeling. Electronic books. Li, Wentao editor. Zhang, Chao editor. IGI Global, publisher. Print version: 9798369315828 |
| spellingShingle | Big data quantification for complex decision-making Preface -- Chapter 1. Group-Oriented Multi-Attribute Decision-Making Method Based on Dominance Rough Set Theory -- Chapter 2. A Multi-Granularity Triangular Fuzzy Approach for Diabetes Blood Glucometer Selection Using PROMETHEE and Three-Way Decision -- Chapter 3. Prediction of Parkinson's Disease Severity Based on Feature Optimization -- Chapter 4. Creating a Data Lakehouse for a South African Government-Sector Learning Control Enforcing Quality Control for Incremental Extract-Load-Transform Pipe -- Chapter 5. Decision-Making Based on Partition Order Product Space -- Chapter 6. Strategy Selection and Outcome Evaluation of Change-Based Three-Way Decisions Based on Reinforcement Learning -- Chapter 7. The Extension of MAIRCA Based on Fuzzy Number: Smart Supplier Selection -- Chapter 8. Review of Chinese Text Mining in Agriculture -- Chapter 9. A Snapshot Survey of Data Acquisition Forms in Multi-Attribute Decision-Making Studies -- Chapter 10. Research on Knowledge Representation and Reasoning Based on Decision Implication -- Compilation of References -- About the Contributors -- Index. Big data. Decision making Data processing. |
| title | Big data quantification for complex decision-making |
| title_auth | Big data quantification for complex decision-making |
| title_exact_search | Big data quantification for complex decision-making |
| title_full | Big data quantification for complex decision-making Chao Zhang, Wentao Li, editors. |
| title_fullStr | Big data quantification for complex decision-making Chao Zhang, Wentao Li, editors. |
| title_full_unstemmed | Big data quantification for complex decision-making Chao Zhang, Wentao Li, editors. |
| title_short | Big data quantification for complex decision-making |
| title_sort | big data quantification for complex decision making |
| topic | Big data. Decision making Data processing. |
| topic_facet | Big data. Decision making Data processing. Electronic books. |
| work_keys_str_mv | AT liwentao bigdataquantificationforcomplexdecisionmaking AT zhangchao bigdataquantificationforcomplexdecisionmaking AT igiglobal bigdataquantificationforcomplexdecisionmaking |